Identification of morphology and/or pathologies is often carried out by taking tissue samples, cultures, or the like and viewing same under a microscope. Histology slides, such as Hematoxylin and Eosin slides (herein, “H&E”) are viewed to determine a cause of illness or detect an illness, presence of a pathogen, or abnormality in a body of a human or other mammal. When viewing a slide, it is easy to miss an item of interest when one is not actively looking for the specific item of interest (such as a pathology) or the variation is slight or small. When viewing a slide covering a large area where one must “scroll” to view under a microscope, it is further easy to miss an important detail.
The prior art has made some attempts to automate the process, but automation comes with risk of false positives or making the system less efficient. Examples of can be seen in U.S. Pat. No. 8,488,863, U.S. Pat. No. 8,897,537, U.S. Pat. No. 8,934,718 and EP 3,140,778 A2, where regions of interest have to be manually identified. For example, the method described in U.S. Pat. No. 8,488,863 requires classification of each pixel of a slide which requires hours of processing per slide. Most importantly, it is not clear that individual pixels provide sufficient predictive power to identify a pattern which is highly predictive of a disease state.
The method described in U.S. Pat. No. 8,897,537 and U.S. Pat. No. 8,934,718 requires that one select region of a slide to be analyzed by an automated process, but such a method leaves intact a problem of human error or missed information. There is a low (almost no) concordance among human pathologists, as shown by Ezgi Mercan, Selim Aksoyy, Linda G. Shapiro, Donald L. Weaverx, Tad Brunye, Joann G. Elmorez, “Localization of Diagnostically Relevant Regions of Interest in WSI”. Further, while it is mentioned that different analysis types may require different models, the disclosure of U.S. Pat. No. 8,897,537 it is unknown, based on the disclosure in this prior art reference, how it is possible for the system or a human to select the appropriate model to apply for each one of the tens of thousands of clinical contexts, e.g., ICD10 codes.
The method described EP 3,140,778 A2 requires that the image analysis is performed only after a region of interest has been identified. Further, it relies on predetermined thresholds to perform the analysis. The methods described in U.S. Pat. No. 8,319,793 rely on object networks to guide the pixel classifier so as to overcome the limited predictive value of individual pixels. The methods described in U.S. Pat. No. 8,319,793 relies on image preprocessing steps without which the effectiveness of the method degrades dramatically.
What is needed in the art is to identify histologies and regions of interest both accurately and quickly. It is desired to take the best that a human can do in making identifications and diagnoses when viewing a slide, as well as improve upon or augment same with the ability of a processor to suggest or recommend same.